issue_comments

Right that's actually desired behavior to begin with so this works out

just note that in the end the result is still 2D with the missing values filled with nan

This worked perfectly, thanks so much!

to get your example to work, use this: python data=pd.DataFrame({'x': [0, 1, 2], 'y': ['a', 'b', 'c'],'z': ['a', 'b', 'c']}) xr.DataArray(data.x, coords={'y': data.y, 'x':data.z}, dims="y") to get both as dimensions, use python df = pd.DataFrame({'x': [0, 1, 2], 'y': ['a', 'b', 'c'],'z': ['a', 'b', 'c']}) ds = df.set_index(["y", "z"]).to_xarray()

This also doesn't work feeding y and z as data.y.values and data.z.values which are 1d arrays.

Ultimately merge to another dataset with the same coordinates. Seems like there's something obvious I'm missing here but I haven't been able to figure out what it is.

Ah I see in this example I need a dataset that's 3x3, let me fix the example and see if it's still relevant to my issue

So that's not possible. You can't have both y and z be 1D coordinate variables for x since x is 1D.

What are you ultimately trying to do after the conversion to DataArray?

@dcherian not quite because I want z and y to both have the star next to them (or bolded in your screenshot) so that they're proper coordinates. I likewise thought that the answer would be as simple as:

data=pd.DataFrame({'x': [0, 1, 2], 'y': ['a', 'b', 'c'],'z': ['a', 'b', 'c']}) xr.DataArray(data.x, coords={'y': data.y, 'x':data.z})

But again, I haven't gotten anywhere this way either and getting the error ValueError: coordinate y has dimensions ('y',), but these are not a subset of the DataArray dimensions ('dim_0',)

ds.rename_dims({"i": "y"})

Is this what you want?

@fujiisoup This method works when trying to add a single coordinate, but what about when you're trying to add multiple coordinates? Example:

``` import xarray as xr ds = xr.Dataset({'x': ('i', [0, 1, 2]), 'y': ('i', ['a', 'b', 'c']),'z': ('i', ['a', 'b', 'c'])}) ds= ds.set_coords(['y','z']) ds.swap_dims({'i':'y','i':'z'}) #doesn't work

ds = xr.Dataset({'x': ('i', [0, 1, 2]), 'y': ('i', ['a', 'b', 'c']),'z': ('i', ['a', 'b', 'c'])}) ds= ds.set_coords('y') ds=ds.swap_dims({'i':'y'}) ds.set_coords('z') #doesn't work either ```

Is there any reason that this is the default behavior? This is a bit frustrating to work with after creating an xarray dataset from pandas.

It might be worth putting a "see also" note in the assign_coords and set_coords documentation for this. I tried searching quite a bit, but did not find this.

Thanks for the suggestion. It sounds a good idea. Do you mind to send a PR for this?

Awesome, thank you @fujiisoup.

It might be worth putting a "see also" note in the assign_coords and set_coords documentation for this. I tried searching quite a bit, but did not find this.

I'm closing this issue, but if you have further issue, do not hesitate to reopen this.

Hi @nedclimaterisk. Thanks for the raising an issue.

In that case, you can use swap_dims,

```python In [1]: import xarray as xr ...: ds = xr.Dataset({'x': ('i', [0, 1, 2]), 'y': ('i', ['a', 'b', 'c'])}) ...: ds ...: ...: Out[1]: <xarray.Dataset> Dimensions: (i: 3) Dimensions without coordinates: i Data variables: x (i) int64 0 1 2 y (i) <U1 'a' 'b' 'c'

In [2]: ds.swap_dims({'i': 'x'}) Out[2]: <xarray.Dataset> Dimensions: (x: 3) Coordinates: * x (x) int64 0 1 2 Data variables: y (x) <U1 'a' 'b' 'c' ```